System and method for compiling high-level language code into a script executable on a blockchain platform

ABSTRACT

Techniques are presented to enable or facilitate the execution of a portion of source code, written in a high-level language (HLL), on a blockchain platform. The technique comprises receiving a portion of source code as input; and generating an output script comprising a plurality of op_codes. The op_codes are a subset of op_codes that are native to a functionally-restricted, blockchain scripting language. The outputted script is arranged and/or generated such that, when executed, the script provides, at least in part, the functionality specified in the source code. The blockchain scripting language is restricted such that it does not natively support complex control-flow constructs or recursion via jump-based loops or other recursive programming constructs.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 16/629,295, filed Jan. 7, 2020, entitled “SYSTEM AND METHOD FOR COMPILING HIGH-LEVEL LANGUAGE CODE INTO A SCRIPT EXECUTABLE ON A BLOCKCHAIN PLATFORM,” which is a 371 National Stage of International Patent Application No. PCT/IB2018/054971, filed Jul. 5, 2018, which claims priority to United Kingdom Patent Application No. 1710967.9, filed Jul. 7, 2017, United Kingdom Patent Application No. 1710971.1, filed Jul. 7, 2017, United Kingdom Patent Application No. 1710974.5, filed Jul. 7, 2017, International Patent Application No. PCT/IB2017/054110, filed Jul. 7, 2017, International Patent Application No. PCT/IB2017/054113, filed Jul. 7, 2017, and International Patent Application No. PCT/IB2017/054114, filed Jul. 7, 2017, the disclosures of which are incorporated herein by reference in their entirety.

The present disclosure relates generally to distributed ledger technologies, and more particularly to blockchain technologies such as, for example, the Bitcoin network and associated protocol. It also relates to compilers and compiler-related technologies for the translation of computer-based code. One or more embodiments of the invention are suited for use as a solution to enable and/or facilitate the automation and execution of high-level programs on a blockchain platform or protocol which comprises a functionally-restricted script-based language.

In this document we use the term ‘blockchain’ to include all forms of electronic, computer-based, distributed ledgers. These include consensus-based blockchain and transaction-chain technologies, permissioned and un-permissioned ledgers, shared ledgers and variations thereof. The most widely known application of blockchain technology is the Bitcoin ledger, although other blockchain implementations have been proposed and developed. While Bitcoin may be referred to herein for the purpose of convenience and illustration, it should be noted that the invention is not limited to use with the Bitcoin blockchain and alternative blockchain implementations and protocols fall within the scope of the present invention. The term “user” may refer herein to a human or a processor-based resource.

A blockchain is a peer-to-peer, electronic ledger which is implemented as a computer-based decentralised, distributed system made up of blocks which in turn are made up of transactions.

Each transaction is a data structure that encodes the transfer of control of a digital asset between participants in the blockchain system, and includes at least one input and at least one output. Each block contains a hash of the previous block to that blocks become chained together to create a permanent, unalterable record of all transactions which have been written to the blockchain since its inception. Transactions contain small programs known as scripts embedded into their inputs and outputs, which specify how and by whom the outputs of the transactions can be accessed. On the Bitcoin platform, these scripts are written using a stack-based scripting language called Script. The scripts are written using commands (op_codes) which are converted into executable code by the interpreter.

In order for a transaction to be written to the blockchain, it must be “validated”. Network nodes (miners) perform work to ensure that each transaction is valid, with invalid transactions rejected from the network. Software clients installed on the nodes perform this validation work on an unspent transaction (UTXO) by executing its locking and unlocking scripts. If execution of the locking and unlocking scripts evaluate to TRUE and possibly other checks pass, the transaction can be deemed valid and the transaction can be mined for inclusion in the blockchain. Thus, in order for a transaction to be written to the blockchain, it must be i) validated by the first node that receives the transaction—if the transaction is validated, the node relays it to the other nodes in the network; and ii) added to a new block built by a miner; and iii) mined, i.e., added to the public ledger of past transactions.

Although blockchain technology is most widely known for the use of cryptocurrency implementation, digital entrepreneurs have begun exploring the use of both the cryptographic security system Bitcoin is based on and the data that can be stored on the Blockchain to implement new systems. It would be highly advantageous if the blockchain could be used for automated tasks and processes which are not limited to the realm of cryptocurrency. Such solutions would be able to harness the benefits of the blockchain (e.g., a permanent, tamper proof records of events, distributed processing, etc.) while being more versatile in their applications. Thus, there is a need for wider adoption of the technology for new applications and technical innovations, similar to the adoption of the internet in its early days and the subsequent boom in development of web-based systems.

However, writing programs in scripting languages such as, for example, is not as intuitive or readily adoptable by the wider programming community because it requires knowledge and skill relating to low-level programming techniques. It requires the programmer to consider the stack(s) and locations of data within them. Writing programs made up of low level op_codes is more time and labour intensive than writing source code in a high-level language (HLL) such as C, Java etc. Compilers/interpreters built for such HLLs provide a convenient layer of abstraction which distances the programmer from the more laborious, lower-level issues relating to memory management etc. Writing sequences of op_codes to manipulate data in one or more stacks is more technically complex and time-consuming than writing source code in an HLL. Therefore, errors and bugs are more likely to occur because of the difficult nature using low-level op_codes.

Moreover, HLLs enable the programmer to include complex control flow structures such as loops, case statements and recursive calls in their source code. The programmer can focus on the desired logic and express logical flows in an intuitive manner with mechanisms such as “while this is true, do X . . . ”. However, some blockchain-associated scripting languages such as Bitcoin's Script, are functionally restricted in the sense that while they include classic operators such as arithmetic operations and also cryptographic functions such as hashing operators and signature verification, they do not include native primitives for complex control structures such as while loops, or allow the use of recursive techniques, as one would be able to use in an HLL. Such a restricted language would not support jump-based control flow. Thus, by design, they restrict the language and logical constructs offered to the programmer for inclusion in the source code. This has led some people to contend that restricted languages such as Script are non-Turing complete, although this definition is contested by others. Therefore, we will use the phrase “functionally restricted”.

It is noted, though that while this deliberate restriction may make the coding process more difficult for the programmer, it results in program execution time is bounded and, importantly, provides a significant security mechanism because it prevents malicious exploits e.g. protects against the use of infinite loops to implement Denial of Service (DoS) attacks.

Therefore, there is a trade-off between crucial security and the need to facilitate, encourage and improve the development of blockchain-based technologies. In order to address the latter problem, Ethereum incorporates a HLL language as a native feature in its blockchain platform. As with Script, a lower-level interpreter is required to produce the executable version of the code. Ethereum's HLL language, known as Ether, allows control-flow to be executed through the use of conditional and unconditional jumps. It also allows recursion. In order to avoid problems such as DoS attacks, Ethereum limits transaction execution time by introducing the concept of gas—a portion of cryptocurrency that is paid in advance to cover execution costs. Thus, an additional layer of technical and commercial complexity is required because of the use of a native HLL. Additionally, Ethereum has suffered from at least one significant, recursion-based attack to date. See, for example the Dao exploit, such as available at: hackingdistributed.com/2016/06/18/analysis-of-the-dao-exploit/

Thus, it is desirable to provide a mechanism by which programmers can develop, design and produce valid blockchain solutions in an easier, quicker and more efficient manner, using HLL languages that they are familiar with, but without compromising the security provided by functionally-restricted scripting languages. This is by no means a trivial task, which requires a significant degree of technical innovation. It is, among others, one of the technical problems addressed by the present disclosure.

Thus, in accordance with the present disclosure, there is provided a system(s) and corresponding method(s) as defined in the appended claims.

In accordance with the present disclosure there may be provided a computer-implemented method and corresponding system(s). The method may be arranged to enable or facilitate the execution of a portion of source code on a blockchain platform. The source code may be written in a high level language. The present disclosure describes a compilation technique and system/component, which may be implemented as a software compiler. It may be referred to hereafter as a “blockchain or Bitcoin compiler”. The software compiler may be arranged for use in conjunction with the Bitcoin blockchain or any other blockchain-based protocol/network.

Advantageously, the software compiler of the present disclosure may enable a user (programmer) to write and create blockchain-executable programs/applications in a language which is familiar to them, e.g., in a C, Java, C++ style of syntax. This opens up the task of blockchain-based development to a wider development community. It also means that blockchain-based solutions can be written more swiftly and can be error-checked by the invention as discussed in more detail below. Crucially, the security features of the underlying protocol and associated scripting language are preserved and maintained. Thus, the invention provides techniques and systems for preserving blockchain-related security during process of script generation, and facilitates or enables the generation of valid, error free scripts (and thus transactions) which validated by nodes on a blockchain network.

In accordance with one possible embodiment, a computer-implemented method may be provided that uses static compilation to translate a portion of source code into a blockchain-compatible script. This may be referred to as an “output script” as it may form the output provided by the compiler. The invention may test for one or more errors. It may provide an alert if one or more errors is detected. The static compilation may comprise the step of loop unrolling; one or more loops provided within the portion of source code may be unrolled. It is noted that the terms “static compilation” and “loop unrolling” are terms known in the art and as they are readily understood by a person skilled in the art.

The method may be arranged for use with a blockchain network. The blockchain network may be associated with a protocol. It may be a “proof-of-work” blockchain. It may be a consensus-based blockchain. It may be a public and/or un-permissioned blockchain. It may be a peer-to-peer, decentralised blockchain.

The blockchain network may which comprise a plurality of nodes that validate blockchain transactions. The blockchain transactions may include scripts that can be executed by the plurality of nodes. The scripts may be represented by, or comprise, a set of op_codes belonging to a functionally-restricted (or otherwise referred to as a non-Turing complete”) blockchain scripting language. The method may comprise the step of generating the output script for incorporation into a blockchain transaction validated by the nodes of the blockchain network. The output script may be represented by the set of op_codes belonging to the functionally-restricted blockchain scripting language, and the output script may be arranged or adapted such that execution of the script by the nodes of the blockchain network performs the functionality specified in the source code.

The portion of source code may be written in a high level language (HLL). The HLL may be described as a compilable HLL. The HLL may be compiled by a software component (compiler) arranged in accordance with the present invention. The HLL may be compiled by the compiler to produce a script which can be executed by an interpreter. The script may be provided in a blockchain transaction (Tx). It may be associated with an input or output of the transaction. The HLL may be a Turing complete language (subject to real world constraints) in that it may permit expressions, constructs and/or statements which implement complex control flows such as recursion, complex selection structures and/or loops. The syntax native to the HLL may include loop-related syntax such as WHILE, FOR or REPEAT loops. It may comprise primitives for the performance of cryptographic, arithmetic and stack-manipulation operations. The HLL may comprise customised Op_codes and/or high level language constructs, substantially as described below.

The blockchain compatible script may be a script (i.e., program) which is formed of op_codes that are selected from, are native to, and/or form part of a blockchain scripting language which can be executed on a blockchain. The op_codes may be referred to as primitives or commands. The script may be passed through an interpreter or Virtual Machine before being executed/executable on the blockchain. (The term “blockchain” in this context may include the protocol and implementing platform). The interpreter may translate the script into machine-executable (object) code. The blockchain scripting language may be, for example, the Script language as used in conjunction with the Bitcoin protocol or a variation thereof. The scripting language may be arranged for use with a blockchain protocol. The scripting language may comprise cryptographic, arithmetic and stack-manipulation op_codes.

The blockchain scripting language may be functionally restricted. It may be restricted in respect of the functionality that syntax/interpreter are arranged to permit or handle. It may not natively support complex control flows such as recursion, complex selection structures and/or loops.

Additionally or alternatively, a method can be provided that is arranged to enable or facilitate the execution of a portion of source code, written in a high-level language (HLL), on a blockchain platform. The source code may be arranged to implement a smart contract. The smart contract may be a machine readable and executable application, executable on a blockchain as known in the art.

The method may comprise the step of receiving the portion of source code as input. It may be received by a software-implemented compiler.

The method may comprise the step of generating an output script. This may be a blockchain-compatible script as described above. It may comprise a plurality of op_codes selected from and/or native to a functionally-restricted, blockchain scripting language. This scripting language may be as described above. When executed, the script may provide, at least in part, the functionality specified in the source code.

The method may comprise the step of providing or using a compiler arranged to perform any embodiment of the method(s) described above. The output script may be generated by performing a static compilation.

The use of static compilation provides the advantage that the resulting script will always halt. Not only does this provide practical advantages at run-time, it enables the invention to serve as a validation tool because the blockchain compiler will stop if some type of error or invalid construct is encountered in the source code. The advantage of being able to use a validation tool during script development means that the programming task is enhanced by reducing programmer time and effort. Further still, the blockchain compiler provides a security solution in that it tests for bugs and overflow errors, enabling the user (programmer) to statically test whether the program will execute and execute safely.

The blockchain scripting language may be restricted such that it does not natively support complex control-flow constructs or recursion via jump-based loops or other recursive programming constructs. The step of generating the output script may comprise unrolling at least one looping construct provided in the source code. The method may comprise the step of providing or using an interpreter or virtual machine arranged to convert the output script into a form that is executable on a blockchain platform.

The method may further comprise the step of optimising the output script at least once to provide a more efficient or reduced version of the output script. This may involve the use of derivative free optimisation (DFO). DFO is a term known in the art and readily understood by a person skilled in the art. Additionally or alternatively, the step of generating the output script may comprise the use of derivative free optimisation.

The blockchain compiler may be arranged to form part of, and/or operate in conjunction with, a software development kit (SDK). The SDK may comprise an editor, a debugger and other component(s) known to be used with an SDK to facilitate the generation of code-based solutions.

The HLL may comprise at least one primitive, operator or construct which can be translated directly into one or more primitives/commands/op_codes native to the blockchain scripting language.

The blockchain scripting language may be stack-based. It may be arranged to manipulate one or a plurality of stacks. The HLL may comprise one or more primitives or operators arranged to cause the performance of an operation on a stack used by the scripting language.

The HLL may comprise a primitive or construct arranged to push a number of inputs to the source code onto a stack used for memory allocation by the blockchain scripting language. The HLL may comprise one or more primitives arranged to cause the execution of cryptographic operation or function, and arithmetic operation, and/or a loop.

The HLL may comprise at least one of the following primitives or operators or their respective functional equivalent:

-   -   Initiate;     -   Declare;     -   Increment;     -   IF;     -   While;     -   Populate;     -   Monus;     -   Reset;     -   Rawscript;     -   Abort;     -   Retrieve     -   Hash, hash 160, or another hash operation or a variation         thereof.

The present disclosure may provide a method comprising the step of using static compilation to translate a portion of source code into a blockchain-compatible script. The static compilation may comprise the step of loop unrolling.

The portion of source code may include at least one high level programming construct. The output script may be generated by translating the high level programming construct into one or more op_codes belonging to the functionally-restricted blockchain scripting language. The one or more op_codes of the output script may be arranged or adapted such that execution of the one or more op_codes by the nodes of the blockchain network performs the (functionality of) at least one high level programming construct of the source code.

Preferably, the functionally-restricted blockchain scripting language does not support loop constructs. Preferably, the at least one high level programming construct comprises a loop construct. Preferably, the script is generated by unrolling the loop construct (which may also be referred to as a “looping construct”). Preferably, the loop construct includes a block of code and an argument specifying a number of iterations, and unrolling the loop construct involves writing op_codes for functionality of the block of code for the number of iterations.

The method may further comprise the step of checking syntax of the loop construct to ensure that the loop construct includes an argument specifying a number of iterations and that such argument satisfies a constraint specifying a maximum number of iterations.

-   -   The loop construct may include a block of code and a condition         for specifying a number of iterations of the loop construct         based on at least one variable. Preferably, unrolling the loop         construct involves replicating op_codes for the functionality of         the block of code in conjunction with writing op-codes commands         that selectively execute the replicated op_codes for the         functionality of the block of code for a maximum number of         iterations based on evaluation of the condition using a value of         the variable determined from execution of the output script.

In accordance with the present disclosure, there is provided a computer-implemented system arranged to implement the steps of any embodiment of the method(s) described herein.

A computer-implemented system in accordance with an embodiment of the present disclosure may comprise a compiler. The compiler may be arranged to receive a portion of source code as input. The source code may be written in a high-level language (HLL). The compiler may be arranged to generate an output script. The output script may be referred to as a “blockchain script” or “blockchain compatible script” and may comprise a plurality of op_codes. These op_codes may be selected from, and/or native to, a functionally-restricted, blockchain scripting language as described above such that, when executed, the script provides, at least in part, the functionality specified in the source code.

The system may comprise a software development kit (SDK). The compiler may form part of the DSK.

The invention also provides a system, comprising:

-   -   a processor; and     -   memory including executable instructions that, as a result of         execution by the processor, causes the system to perform any         embodiment of the computer-implemented method described herein.

-   The invention also provides a non-transitory computer-readable     storage medium having stored thereon executable instructions that,     as a result of being executed by a processor of a computer system,     cause the computer system to at least perform an embodiment of the     computer-implemented method described herein.

Any feature(s) described above in relation to one aspect or embodiment of the present disclosure may also apply to one or more other aspects or embodiments. Any feature described in relation to a method of the present disclosure may apply equally to a system in accordance with the present disclosure, or vice versa.

These and other aspects of the present disclosure will be apparent from and elucidated with reference to, the embodiment described herein. An embodiment of the present disclosure will now be described, by way of example only, and with reference to the accompany drawings, in which:

FIG. 1 illustrates an overview of the present invention.

FIG. 2 provides the block of code for the populating the Try[ ] array as discussed in relation to the example below for unrolling a while loop.

FIG. 3 illustrates a blockchain environment in which various embodiments can be implemented.

FIG. 4 illustrates a blockchain protocol for validating and mining a spending blockchain transaction that references a previous blockchain transaction in accordance with an embodiment;

FIG. 5 illustrates a computing environment in which various embodiments can be implemented.

OVERVIEW

Hereafter, we may refer to the Bitcoin protocol, blockchain, network or scripting language for ease of reference only, as it is the most widely known and adopted. However, the invention is not limited for use with Bitcoin-related blockchains, and other blockchain technologies fall within the scope of the present disclosure.

As discussed above, the majority of programmers today write code in High Level Languages such as C, C++ Java etc., rather than at low level. Writing code at the lower level takes more time, requires more specialised knowledge of memory manipulation, and errors can be introduced as a result. Therefore, it would be advantageous for programmers to be able to write valid, tested and error-checked code for blockchain applications in a language which is more familiar to them, without compromising the security provided by the underlying, restricted scripting language.

The methods and systems as described in the present disclosure enable the development of an ‘SDK’ for the creation of specialised blockchain transactions or clusters of transactions. For example, the transactions may be intended to automatically enforce the terms and conditions of machine executable smart contracts, although many other applications are possible and the invention is not limited in this regard. Thus, the invention may form part of “toolkit” or system for creating and testing blockchain-related technologies.

Advantageously, the blockchain compiler performs static compilation of the user's source code, and enables the implementation of complex control flow mechanisms via the use of techniques such as loop unrolling. As known in the art, “loop unrolling” may also be referred to as “loop unwinding”. Loop unrolling is a loop transformation technique which can be used by compilers to reduce the frequency of branches in certain types of loops, and/or to reduce loop maintenance instructions. By unrolling loops found in the source code, the compiler can produce a translated version of the source code which is executable on a blockchain platform which uses a functionally restricted scripted language.

Turning to FIG. 1 , an embodiment of the present disclosure enables the user (programmer) to use a high level language (HLL) to define the code 101 for the desired application e.g. smart contracts and then execute a blockchain compiler 102 which compiles the HLL code 101 into executables. These executables may be in the form of chunks of 3G languages programs (such as python, C++, etc.) that can be executed by bots, or they might be in the form of chunks of (e.g. Bitcoin) script 103. The latter is achieved by designing and generating chunks of script that can perform specific functions. For example, the original version of Bitcoin script included a function for multiplication called OP_MUL. This op_code is currently disabled. However, the same functionality can be recreated by using the existing, enabled op_codes in a small portion of script.

Embodiments of the present disclosure may comprise one or both of two types of primitive:

-   -   Customised op_codes (which we will refer to hereafter as         COP_CODEs); and     -   High level Language (HLL) constructs

HLL constructs require a compiler 102 to translate them into script code 103, while COP_CODEs require only a direct substitution from the COP_CODE to the block of OP_CODEs. Typically, a primitive is made into a COP_CODE if it does not require access to any variables—that is, if it can be completely described using only OP_CODEs which already exist in the blockchain scripting language for a given protocol (and other COP_CODEs) and hard-coded inputs.

For example, the monus primitive can be fully described with op_codes and so can be made into a COP_CODE, as follows:

  OP_SUB OP_0 OP_MAX

However, the execution of a WHILE loop depends on required variables (for example, the condition for execution; a counter for the number of iterations; etc.). Therefore, WHILE is not suitable to be made into a COP_CODE and would be written as a HLL construct.

Advantageously, the incorporation of two types of primitive provides additional flexibility for the programmer. Programmers that will be writing programs directly into Bitcoin script (i.e. not using a HLL) will be able to use enhanced script functionality by way of the COP_CODEs. In effect, these give the script programmer a substitution for the block of OP_CODEs that will perform the function they need, cutting down on programming time and effort. All that is needed is a ‘COP-CODE compiler’ which simply substitutes the COP_CODE with the block of OP_CODEs that constitute it. Programmers unable or unwilling to write programs in the low level bitcoin script are able to use the HLL supported by the present disclosure instead.

The Customised OP_Codes (COP_Codes) are further discussed below.

1. Customised OP_CODEs (COP_CODEs)

This section describes the standards that may be applied hereafter and in accordance with the present disclosure in relation to script primitives for Customised OP_CODEs (COP_CODEs). COP_CODEs are given similar format to the regular op_codes and operate in the same way. That is, writers of Script (and/or compilers) use primitives in the same way as one would conventionally use op_codes. A list of Bitcoin op_codes can be found at the Bitcoin wiki: https://en.bitcoin.it/wiki/Script.

Naming Conventions

Script primitives are named herein analogously to Bitcoin Script op_codes, as follows:

COP_xxx

Where ‘xxx’ is a shorthand for the function. For example, a multiplication function might be named: COP_MULT. Also analogously to op_codes, if a function has specific number of parameters or a specific number used in a calculation, the name may incorporate that number.

For example, the op_code ‘OP_2DROP’ means ‘Removes the top two stack items’ while ‘OP_1ADD’ means ‘1 is added to the input’. Therefore, COP_2MULT might mean specifically ‘The input is multiplied by 2’.

Validation Prior to Execution

In cases where a specific number of inputs or format of inputs is expected, the primitive performs a check prior to executing the functional logic, and aborts (marks the transaction as invalid) if the inputs do not match expectations. Advantageously, this prevents functions from executing and providing an output that might be incorrect or misleading. For example, if a particular primitive is intended to operate only on inputs that are positive numbers but nevertheless will execute without error on negative numbers then the result might be a ‘valid transaction’ but with an unexpected or incorrect result.

2. High Level Language (HLL) Constructs

These are functions or statements that a compiler ranged in accordance with the present disclosure is able to recognise and be able translate into Bitcoin script. Taken all together these constitute a high level programming language using syntax familiar to programmers. As well as the familiar constructs (such as IF-ELSE; CASE; WHILE loops; etc.) there are also unfamiliar constructs very specific to the HLL because of the way bitcoin transactions work. For example, an INITIATE construct performs a very specific function which is to ensure the number of data inputs automatically pushed to the main stack is saved as the first constant in the memory allocation (assigned to reserved word NUM_INPUTS). In embodiments, the INITIATE construct can be the first statement in a HLL program and the DECLARE construct (which performs the memory allocation for constants and variables) can be the second statement in the HLL program.

A HLL construct must be designed in such a way that it can be translated into Bitcoin script (i.e., into OP_CODEs and COP_CODEs) by a compiler using only the information available at compilation time. That usually means a lot of hard-coding by the programmer, in which constants are DECLARE'd and assigned values in the program. For example, even though NUM_INPUTS is considered a constant a compiler will not have access to its value until the program executes, so this cannot be used for compilation execution (although of course the programmer can use it like any other constant in the program).

When designing a HLL construct, the designer can include the expected operations of the compiler in pseudocode or a clear explanation in natural language. For example, the compiler might be required to perform certain checks—such as correct syntax and verifying compliance with any constraints (such as size limitations). This should be explicit even though the specific constraints may not be known yet. The task of designing HLL constructs does not include writing the compiler itself but must ensure that all the expected operations of the compiler will be possible.

A selection of HLL constructs which may be used in accordance with an illustrative embodiment of the present disclosure is now provided.

HLL Construct: While Loop

Description

A block of code (or code-block, which is typically referred to as the loop body) will be repeatedly executed as long as a specified condition remains True, up to a maximum number of iterations. The maximum number of iterations must be known and specified at compile time. The loop is emulated by the technique known as ‘unrolling the loop’. This means that a sequence of op_codes that represent the functionality (sequence of operations) of the code-block is replicated to the specified maximum number of iterations. An IF statement prior to each replicated sequence of op_codes for the code-block determines if the sequence of op_codes for the code-block gets executed. The IF condition is checked at the start of the loop (i.e. before first execution of the sequence of op_codes for the code block).

Syntax:

  WHILE (Iterations, Condition)  <CODE-BLOCK> END_WHILE Where: Iterations:

-   -   A positive integer     -   the maximum number of times the Code-Block could be executed.         The compiler needs to know this value because it will generate         the Code-Block up to this many times. It could be hard-coded, or         it could refer to a constant that is in the DECLARE statement.         Condition:     -   An evaluable expression that resolves into TRUE or FALSE     -   May be a compound condition—i.e. using AND, OR, etc. (whichever         is currently recognised by the compiler)         Compiler Operations:         Perform syntax checking.     -   Check that Iterations satisfies any constraints (e.g. falls         within a prescribed range)     -   Check that the expression(s) in Condition is evaluable:         -   All constants/variables in the expression exist in the             memory allocation (DECLARE) list         -   Check that all operators used in the expression are             currently allowed (=, <, >, etc.)         -   Check that compound expressions satisfies any constraints             (e.g. limited ANDs, ORs, etc.)             Replicate the functionality of the Code-Block ‘Iterations’             times:             Start of Replicated Code

Write one or more op_codes that the resolve the Condition (i.e. whose execution leaves TRUE or FALSE on top of the stack):

-   -   The general process can employ a RETRIEVE construct that fetches         each value required for the test and places the value on top of         the main stack; then perform the relevant test operation (i.e.         OP_EQUAL; OP_LESSTHAN; OP_GREATERTHAN; etc.). If a value to be         tested is a constant then it will be in a known location in the         allocated memory (i.e., a known position on the main stack) and         will be copied to the top of the stack using OP_PICK. If the         value to be tested is a variable (in this case, the value to be         tested is determined during script execution), then the location         of the variable will be in a known location in the allocated         memory (i.e., a known position on the alt stack) and can be         copied to the top of the main stack using a ‘Borrow Block’         method.     -   If the test employs a compound condition (using AND, OR, etc.),         each subcondition will be separately evaluated and the         end-result (0 or 1) left on top of the main stack. These will         then be combined to test the compound condition. For example, if         the compound condition is of the form ‘Exp1 OR Exp2’: the         operations first evaluate Exp1 then evaluate Exp2 then write         OP_BOOLOR which will compare the top two values on the stack         (i.e. the evaluation results for Exp1 and Exp2).     -   The result of the evaluation is left on top of the main stack.         No other values are on the stack (except of course for the         allocated memory). The value will be consumed by the next         operation (OP_IF).

Translate the functionality (sequence of operations) of the Code-Block into a sequence of op_codes that represent the functionality of the Code-Block. Such translation can be bypassed for any COP_CODE included in the Code-Block, which requires only a direct substitution of the COP_CODE into the sequence of op_codes for the Code-Block. Then write the sequence of op_codes that represent the functionality of the Code-Block within an OP_IF/OP_ENDIF pair

End of Replicated Code

In some embodiments, the sequence of op_codes that represent the replicated Code-Block can be configured such that the initial stack positions for constants and variables that are accessed by the sequence of op_codes for each iteration of the WHILE Loop construct is constant over the loop iterations. Note that the value(s) of the variable(s) can be updated over the loop iterations; however, the stack positions for such constants and variables when beginning execution of each loop iteration will remain constant over the loop iterations. Such operations ensure that the replicated sequence of op_codes access the appropriate constants and/or variables stored on the stacks during each loop iteration.

In some embodiments, the Condition for replicating the Code-Block can be dependent on the value of one or more variables which are determined during script execution and thus can be updated over the loop iterations. In this case, each iteration of the replicated Code-Block can include one or more op_code commands that test the relevant Condition followed by the sequence of op_codes that represent the replicated Code-Block embedded within an OP_IF/OP_ENDIF pair. In this configuration, during execution of the script, the op_code commands that test the relevant Condition will evaluate as TRUE or FALSE and place the TRUE or FALSE result on top of the stack. The execution of the following OP_IF statement will selectively execute the replicated Code-Block only when the TRUE result is on top of the stack. Thus, when the FALSE result is on top of the stack, the execution of OP_IF statement bypasses the execution of the replicated Code-Block.

Furthermore, the Condition for replicating the Code-Block can be bounded by a maximum number of iterations, which can be defined by a parameter specified in the WHILE Loop construct, a parameter fixed by system design or some other parameter. In this case, the op-code commands that test the Condition and the following sequence of op_codes that represent the replicated Code-Block embedded within the OP_IF/OP_ENDIF pair can be replicated a number of times corresponding to the parameter-defined maximum number of iterations.

Also note that the HLL program can employ nested WHILE Loop constructs where an inner WHILE Loop construct is contained within the Code-Block of an outer WHILE Loop construct. In this case, the compiler can perform loop unrolling for the inner WHILE Loop construct in conjunction with loop unrolling for the outer WHILE Loop construct. For example, the loop unrolling of the inner WHILE Loop construct can replicate a sequence of op_codes that represents the functionality of the Code-Block of the inner WHILE Loop construct between a pair of OP_IF/OP_ENDIF bytecode instructions for a number of iterations of the inner WHILE Loop construct. Furthermore, the loop unrolling of the outer WHILE Loop construct can replicate a sequence of op_codes that represents the functionality of the Code-Block of the outer WHILE Loop construct between a pair of OP_IF/OP_ENDIF bytecode instructions for a number of iterations of the outer WHILE Loop construct. In this case, the sequence of op_codes that represents the functionality of the Code-Block for each iteration of the outer WHILE Loop construct will include the op_code sequences for the number of iterations of the inner WHILE Loop construct.

Also note that the WHILE Loop nesting can be extended where an additional inner WHILE Loop construct is contained within the Code-Block of the inner (first inner) WHILE Loop construct and with possible further nesting. In this case, the loop unrolling operations as described herein can be readily extended to address this further nesting.

HLL Construct: INITIATE

Description:

In embodiments, this is the mandatory first statement of any HLL program.

The first part of a script execution as supplied by the transaction spender (i.e., the ‘scriptsig’) is outside the control of the unlocking script. It usually consists of data that will be pushed to the stack. The purpose of the INITIATE construct is to enable the programmer to manage this input (whether or not it is required for the rest of the script, as is most likely).

This construct ‘allocates a value’ to the reserved word NUM_INPUTS (being the number of items in the spender-provided input that gets pushed to the stack). The first OP_CODE will always be OP_DEPTH so that the top of the stack (at this point) contains the number of data inputs that were pushed to the stack. This position in the stack will be fixed and known to the compiler at compilation time, although the actual value will not be known at compilation time.

Syntax:

INITIATE

Compiler Operations:

Write OP_DEPTH/*this sets OP_DEPTH to the value of NUM_INPUTS

HLL Construct: DECLARE

Description:

In embodiments, the is the mandatory second construct of any HLL program.

Declare all constants and variables so the compiler can reserve ‘memory storage’ (i.e. positions in the main and/or alt stacks). The standard is to keep constants on the main stack and variables on the alt stack. The compiler will associate the names given to the variables and constants to their positions on the stack. The compiler will push the named items onto the main stack, which already contains the data input provided by the spender (see INITIATE) and on top of that a value representing the number of those data items (which it associates to the reserved word NUM_INPUTS).

Syntax:

DECLARE  CONSTANTS = Initial-value   Const-name Initial value (if same for all elements)   Array-nameA[array-size] = initial value for element 1   Array-nameB[1] = initial value for element 2   Array-nameB[2] =    ...   Array-nameB[n] = initial value for element n   VARIABLES   Var-name = Initial-value   Array-nameC [array-size] = Initial value (if same for all elements)   Array-nameD[1] = initial value for element 1   Array-nameD[2] = initial value for element 2    ...   Array-nameD[n] = initial value for element n END_DECLARE Compiler Operations:

Write PUSHDATA commands to put the DECLARE'd constant values of the HLL program into memory storage (such as the main stack). The commands can begin at the top and push the items into the memory storage one by one. The compiler can keep track of the location (e.g., main stack position) of each constant value in the memory storage.

Write OP-TOALTSTACK commands to put variables of the HLL program into the memory storage (such as the alt stack). Again, the compiler can keep track of the location (e.g., alt stack position) of each variable in the memory storage.

Example:

  DECLARE  CONSTANTS   Stock [5]  = 0  /* Array of 12 values all initialised to 0   Stock_Needed    = 3  /* hard-coded per rules   NUM_Hashes    = 4  /* hard-coded per rules           /* array of 10 hash values hardcoded:   HASH_SAVED[1] = 20-byte hash value   HASH_SAVED[2] = 20-byte hash value   HASH_SAVED[3] = 20-byte hash value   HASH_SAVED[4] = 20-byte hash value  VARIABLES   Stockcounter = 0   Trycounter = 0   HashCounter = 0   MatchFound = FALSE

Following the compiler execution of these statements (and assuming the mandatory INITIATE statement will pick up some values) the state of the memory storage (in this case, main stack and alt stack) will be something like this:

(for temp variables) HASH_ (20 byte SAVED[4] hash) HASH_ (20 byte SAVED[3] hash) HASH_ (20 byte SAVED[2] hash) HASH_ (20 byte SAVED[1] hash) Num_Hashes 4 Stock_Needed 3 Stock[5] 0 Stock[4] 0 Stock[3] 0 Stock[2] 0 Stock[1] 0 NUM_INPUTS n INPUTn 0 Match_Found . . . 0 Hash_counter INPUT2 0 Try_counter INPUT1 0 Stock_counter Stack Alt (Constants) (Variables)

In this example we assume there will be some number of input items supplied to the unlocking script. At the very least, there will be a value in the position labelled ‘NUM_INPUTS’ (this is a reserved word) even if that value is 0 and there are no values on the stack below it. This value will be considered as the start of the memory block, irrespective of how many items are below it. The compiler knows the number of items in memory and their initial relative position from the top of the stack. These items will remain in position for the duration of the program execution. Temporary calculations are done using the space on top of the stack (shown in the diagram as ‘(for temp variables)’). When items are temporarily pushed onto the top of the main stack for calculations, this changes the relative position of the memory items. However, the compiler will always retain knowledge of the relative position.

For example, after the DECLARE statement is executed the compiler will compute and internally retain the value for the Init-depth (in our example Init-depth=12) and the depth position for each item in the stack. i.e.: Init-Depth-Num_Hashes=5 Init-Depth-NUM_INPUTS=12 Init-Depth-Stock[i]=11−i+1 The compiler will be able to calculate the depth of any item at any point during the compilation based on the <item's initial depth>+<number of items added onto the stack>. HLL Construct: INCREMENT Description:

A variable will be retrieved from its location in memory; incremented by 1; and then replaced in its location in memory.

Syntax:

INCREMENT (Variable-name)

Where:

Variable-name:

-   -   The name used in the Declaration section to identify the         variable.         Compiler Operations:

Note: the compiler maintains knowledge of the varying number of items on both stacks (say: Main_Stack_Height and ALT_Stack_Height). The compiler also knows the positions of each variable and constant on each stack, which is established during the Declaration section. i.e. Var-Posn=the position of Variable-name in the alt stack (i.e. the number of items up from the bottom of the stack).

The operation uses the Borrow Block technique.

Calculate Var-Depth = ALT_Stack_Height - Var-Posn + 1 Write OP_FROMALTSTACK Var-depth times /* get the required variable to top of main stack Write OP_ADDI /* increment the value by 1 Write OP_TOALTSTACK Var-depth times /* Replace all borrowed variables back to alt stack (see example 2 in the Borrow Block description). Example: Increment Variable B

F E D C Const2 B Const1 A MAIN ALT

The task is to increment variable B. The compiler knows that the depth of B in the alt stack is: B-Depth=5. The compiler generates the following script code:

OP_FROMALTSTACK    /* Move top of alt to main stack 5 times (i.e. B_Depth times) OP_FROMALTSTACK OP_FROMALTSTACK OP_FROMALTSTACK OP_FROMALTSTACK B C D E F Const2 Const1 A MAIN ALT OP_ADD1    /* Increment the value on top of the main stack by 1 B+1 C D E F Const2 Const1 A MAIN ALT TO-ALTSTACK   /* Return variables to the alt stack TO-ALTSTACK   /* i.e. perform TO_ALTSTACK B-Depth times TO-ALTSTACK TO-ALTSTACK TO-ALTSTACK F E D C Const2 B+1 Const1 A MAIN ALT HLL Construct: IF ELSE Description: Standard IF Test Syntax:

  IF Value1 test-operation Value2  TRUE-CODE-BLOCK ELSE  FALSE-CODE-BLOCK END_IF Where:

-   -   Value1 a hardcoded value or a variable name or constant name     -   Value2 a hardcoded value or a variable name or constant name     -   Test-operation a mathematical test operator such as ‘=’; ‘<’;         ‘>’; ‘≤’; ‘≥’ (etc.)         Compiler Operations:         Check the syntax. Including:

 Match test-operation to equivalent OP CODE (internal table):    = OP_EQUAL    > OP_GREATERTHAN  <  OP_LESSTHAN  (etc.) If Value1 is a variable or constant:  Write RETRIEVE Value1 /* leaves Value1 on top of stack Else (it’s a number)  Push Value1 top of stack If Value2 is a variable or constant:  Write RETRIEVE Value2 /* leaves Value2 on top of stack Else (it’s a number)  Push Value2 top of stack Write: OP_IF  TRUE-CODE-BLOCK  /* code-block to execute if the test results in TRUE OP_ELSE  FALSE-CODE-BLOCK  /* code-block to execute if the test results in FALSE OP_ENDIF HLL Construct: RESET Description: A variable will be assigned a specified value. Syntax: RESET (Variable-name, Reset-value) Where:

-   -   Variable-name The name of the variable to be assigned a new         value     -   Reset-value The value to be assigned to Variable-name         Compiler Operations:

Note: the compiler maintains knowledge of the varying number of items on both stacks (say: Main_Stack_Height and ALT_Stack_Height). The compiler also knows the positions of each variable and constant in the allocated memory (i.e. on each stack), which is established during the DECLARE section.

Assume Var-Posn=the position of Variable-name in the alt stack (i.e. the number of items up from the bottom of the stack). The operation uses the Borrow Block technique:

Calculate Var-Depth = <current ALT_Stack_Height> - Var-Posn + 1 Write OP_FROMALTSTACK Var-depth times /* Get the required variable to top of main stack Write OP_DROP Reset-value        /* Delete previous value; replace with required value Write OP_TOALTSTACK Var-depth times  /* Replace all borrowed variables back to alt stack HLL Construct: ABORT Description: Mark the transaction as invalid Syntax: ABORT Compiler Operations: Write OP_0 OP_VERIFY HLL Construct: POPULATE Description:

The purpose of this construct is to populate a constant DECLARE'd by the programmer using input from the transaction spender (such as input supplied by execution of the unlocking script of a spending transaction).

The input to the locking script (i.e., the ‘scriptsig’) will push any data onto the main stack. This occurs before the DECLARE construct so these inputs are on the bottom of the stack. The number of stack items (NUM_INPUTS) has been placed on top of them by the (mandatory) INITIATE statement. It is the responsibility of the programmer to verify that the rules of the transaction have been met (e.g. that the right number of inputs have been provided).

Syntax:

POPULATE (Stack-position, Constant-name)

Where:

Stack-position:

-   -   Integer. The position counting downwards from the bottom of the         memory block. Remember that the bottom of the memory block         always contains the item NUM_INPUTS and below this are the input         data that gets pushed onto the stack before the locking script         code is executed.         Constant-Name:     -   The name of the constant to be populated.         Compiler Operations:         Calculate shift-count=number of stack items to be temporarily         moved off the main stack onto the alt stack for safekeeping:         Shift-count=Number of stack items on top of the target item         (Constant-name)         Calculate the Input-depth=<relative height of         Constant-name>+stack-position         Write:         OP_TOALTSTACK (replicate this Shift-count times)         OP_DROP/*discard current value of Constant-name (was presumably         set to 0)         <Input-depth> OP_PICK/*get the value required and place in the         Constant-name position         OP_FROMALTSTACK (replicate this shift-count times)         HLL Construct: RAWSCRIPT         Description:

An array of values representing a valid chunk of bitcoin Script code. The compiler will first validate the array to ensure that it is a valid chunk of script code (including OP_CODEs, COP_CODEs and integers).

The purpose is to allow a programmer to include low level code directly into the Compiler output. This is useful for any functionality that is still easier to code directly into script code than using the currently available HLL constructs.

Syntax:

RAWSCRIPT [Values]

Where:

-   -   Values An array (list) of OP_CODEs, COP_CODEs and their integer         inputs         Compiler Operations:

The compiler first validates that the set of values together constitutes valid bitcoin script. That is, the OP_CODEs are all part of the currently accepted enabled OP_CODEs, the COP-CODEs all exist in our lexicon of COP_CODEs and they all have the expected input values.

Next, the Compiler simply writes out the values into the current location in the output script.

HLL Construct: CALCULATE TEMP

Description:

A valid calculation is done that places the result on top of the main stack. ‘Valid’ means it is one of the function constructs currently available to the HLL. Programmer must write the program so that TEMP is available (i.e. still on top of stack) when it is referenced later. Note that TEMP can only be referenced once. (If it is needed more than once then it should have been DECLARE'd as a variable instead.)

Syntax:

CALCULATE TEMP=expression

Compiler Operations:

Check that expression is valid (is a member of the list of currently available function constructs).

Execute the expression, leaving the result (TEMP) on top of the stack.

Parse the following reference to TEMP—determine if TEMP will indeed be on the top of the stack at the time of the reference: if not throw a compilation error.

Example:

CALCULATE TEMP=HASH160 (123456789)

HLL Construct: HASH160

Description:

This performs the hashing algorithm equivalent to the OP_CODE: OP_HASH160

Syntax:

HASH160 (value1)

Where:

-   -   value1 is either:         -   A hardcoded integer         -   A DECLARE'd constant         -   A DECLARE'd variable             Compiler Operations:             If value1 is a hardcoded number, it is pushed to top of             stack             If value1 is a variable or constant, then is RETRIEVED (put             onto top of stack)             Compiler writes:             OP_HASH160             HLL Construct: RETRIEVE             Description:

A variable or constant will be retrieved from its location in memory and copied top the top of the main stack. The original value will remain unaltered in its current location in ‘memory’.

Syntax:

RETRIEVE (Item-name)

Where:

-   -   Item-name a DECLARE'd variable or constant         Compiler Operations:

Note: the compiler maintains knowledge of the varying number of items on both stacks (say: Main_Stack_Height and ALT_Stack_Height). The compiler also knows the positions of each variable and constant on each stack, which is established during the Declaration section. i.e. Item-posn=the position of Item-name in the stack (i.e. the number of items up from the bottom of the stack). The operation uses the Borrow Block technique. Calculate Item-Depth=Stack_Height−Item-posn+1

If the required item is in the alt stack (i.e. it is a variable) Write OPFROMALTSTACK Item-depth times  /* Get the required variable to top of main stack Write OP_DUP  /* Duplicate the value for later use on the main stack Write the following Item-Depth times:  /* Move the duplicated value to the bottom of the  <Item-Depth + 1>  /*  set of borrowed variables.  OP_ROLL Write OP_TOALTSTACK Item-depth times  /* Replace all borrowed variables back to alt stack If the required item is in the main stack (i.e. it is a constant) Write <Item-Depth> OP_PICK  /* Copy required Constant to top of main stack Example: Retrieve a Copy of Variable C

We assume that the memory allocation looks like this:

F E D C Const2 B Const1 A MAIN ALT

The task is to place a copy of the variable C on top of the main stack. The compiler knows that the depth of C in the alt stack is: C-Depth=4. The compiler generates the following script code:

OP_FROMALTSTACK  /* Move top of alt to main stack 4 times (i.e. C Depth times) OP_FROMALTSTACK OP_FROMALTSTACK OP_FROMALTSTACK C D E F Const2 B Const1 A MAIN ALT OP_DUP        /* Duplicate the value of C to the top of stack C C D E F Const2 B Const1 A MAIN ALT <C_Depth+1> OP ROLL  /* OP ROLL from depth of 5 (i.e. C Depth + 1) <C_Depth + 1> OP ROLL  /* Do this 4 times (i.e. C-Depth times) <C_Depth + 1> OP ROLL <C_Depth + 1> OP ROLL C D E F C Const2 B Const1 A MAIN ALT TO-ALT STACK     /* Return borrowed variables to the alt stack TO-ALT STACK     /* i.e. perform TOALTSTACK C-Depth             times TO-ALT STACK TO-ALT STACK F E D C C Const2 B Const1 A MAIN ALT        /* The required variable value is retained on top of        the main stack Reserved Words Reserved Word: NUM_INPUTS Description:

This is always the bottom constant of the memory block. I.e. it is the ‘first’ item in the block of allocated stack positions. Although it is a constant, it is not known at compile time. Therefore it cannot be used by the compiler for any hard-coded script operations (for example, it cannot be used as a number to count how many OP_TOALTSTACK statements to generate in the compiled code). It is known at execution time, so it can be used by the programmer or compiler for tasks such as condition tests in Loops and IF statements.

Reserved Word: TEMP

Description:

This is a temporary once-off variable that after being calculated is left on top of the stack. It exists to enable the programmer to reference it in calculations. The compiler will check the syntax to ensure that TEMP is still on the top of the stack when it is referenced later in the program.

Reserved Word: CONSTANTS

Description:

This is used in conjunction with the DECLARE construct. It is followed by the list of constants that will be pushed onto the main stack.

Reserved Word: VARIABLES

Description:

This is used in conjunction with the DECLARE construct. It is followed by the list of variables that will be pushed onto the alt stack.

For the purposes of illustration, we now provide a use case example involving a WHILE loop, an example HLL program and the Bitcoin script code that would be compiled from it. The Bitcoin script code employs op_codes that belong to the Bitcoin scripting language Script. Note that Bitcoin script code includes comments, which begin with /* or // as is conventional. These comments need not be part of the Bitcoin script code generated by the compiler, but are included below for purposes of explaining the operations of the compiler in generating the exemplary Bitcoin script code.

While Loop Example—Transaction (Tx)

Consider a blockchain transaction (Tx) that has an internal list of 10 hard-coded hash puzzles. To unlock an output of the Tx the spender needs to provide at least 3 correct hash solutions. The transaction locking script will accept up to 12 tries in the same input (i.e. in the ‘scriptsig’) and they can be in any order. The transaction will hash each input ‘try’ and check if it matches one of the internally stored hash values.

For clarity, consider the legacy way of describing the unlocking script in the INPUT section of a Bitcoin transaction:

<scriptSig> <scriptPubkey>

The first part <scriptSig> is the data and/or OP_CODEs included in a spending transaction in order to unlock the OUTPUT of a previous transaction being spent. The second part <scriptPubkey> is the locking script used in the OUTPUT of the previous transaction being spent.

We will refer to these as follows:

<Spender Input> <locking script>

Assume that Spender Input is TRY1 TRY2 TRY3 TRY4 TRY5

That is, the spender has tried 5 different possible hash solutions, of which only 3 need to be correct in order to unlock the transaction, as per the rules specified above. When the combined <Spender Input> <locking script> is executed the first operations will be whatever is in <Spender Input>, which in this example is simply pushing the 5 data items onto the stack.

In embodiments, the blockchain complier can be configured to optimise the output script at least once to provide a more efficient or reduced version of the output script. This may involve the use of derivative free optimisation (DFO). DFO is a term known in the art and readily understood by a person skilled in the art. Additionally or alternatively, the step of generating the output script may comprise the use of derivative free optimisation.

In embodiments, the blockchain compiler may be arranged to form part of, and/or operate in conjunction with, a software development kit (SDK). The SDK may comprise an editor, a debugger and other component(s) known to be used with an SDK to facilitate the generation of code-based solutions.

FIG. 3 illustrates an example blockchain network 1000 associated with a blockchain in accordance with an embodiment of the present disclosure. In the embodiment, the example blockchain network 1000 is comprised of peer-to-peer distributed electronic devices running an instance of the blockchain protocol. In some examples, the distributed electronic devices are referred to as nodes 1002. An example of a blockchain protocol is a Bitcoin protocol.

The nodes 1002 may be comprised of any suitable computing device (e.g., by a server in a data centre, by a client computing device (e.g., a desktop computer, laptop computer, tablet computer, smartphone, etc.), by multiple computing devices in a distributed system of a computing resource service provider, or by any suitable electronic client device such as the computing device 2600 of FIG. 5 ).

In an embodiment, one or more of the nodes 1002 are communicatively coupled to one or more other of the nodes 1002. Such communicative coupling can employ one or more of wired or wireless communication links as are well known. In the embodiment, the nodes 1002 each maintain at least a portion of a “ledger” of all transactions in the blockchain. In this manner, the ledger is a distributed ledger. A blockchain transaction processed by a node that affects the ledger is validated by one or more of the other nodes such that the integrity of the ledger is maintained.

In an embodiment, at least some of the nodes 1002 are miner nodes that perform a mining process involving complex calculations, such as solving cryptographic problems. A miner node that solves the cryptographic problem creates a new block for the blockchain and broadcasts the new block to others of the nodes 1002. The others of the nodes 1002 perform a verification process that verifies the work of the miner node and, upon verification, accepts the block into the blockchain (e.g., by adding it to the distributed ledger of the blockchain). In some examples, a block is a group of transactions, often marked with a timestamp and a “fingerprint” (e.g., a hash) of the previous block. In this manner, each block becomes linked to a previous block, thereby creating the “chain” that links the blocks in the blockchain. In embodiments, valid blocks are added to the blockchain by a consensus of the nodes 1002. Also, in some examples, a blockchain comprises a list of validated blocks.

In an embodiment, at least some of the nodes 1002 operate as validating nodes that perform a validation process that validates transactions as described in the present disclosure. FIG. 3 shows one exemplary transaction labelled 1004. In some examples, a transaction includes data that provides proof of ownership of a digital asset (e.g., an amount of Bitcoin tokens) and conditions for accepting or transferring ownership/control of the digital asset. In some examples, a “spending transaction” refers to a transaction that re-associates (e.g., transferring ownership or control) at least a portion of a digital asset, indicated by an unspent transaction output (UTXO) of a previous transaction, to an entity associated with a blockchain address. In some examples, a “previous transaction” refers to a transaction that contains the UTXO being referenced by the spending transaction. In some embodiments, the transaction can include an “unlocking script” and a “locking script.” The locking script can be used to encumber the transaction with conditions that must be fulfilled before the transaction is validated and ownership/control is transferred by the transaction. In some embodiments, the locking script can be associated with an output of the transaction and can be configured to define one or more conditions needed to spend the output. Furthermore, the unlocking script of the spending transaction can be configured such that execution of the unlocking script provides data that is used to derive a set of conditions evaluated by the execution of the locking script of the previous transaction for validation of the spending transaction. The locking script of the previous transaction and the unlocking script of the spending transaction are written using a low level functionally-restricted scripting language, such as Bitcoin's Script.

In some embodiments, validation of a spending transaction may involve executing the unlocking script of spending transaction together with executing the locking script of the previous transaction in order to satisfy and validate a set of conditions dictated by the locking script of the previous transaction. The validation of the spending transaction can involve other checks. Upon successful validation of the spending transaction, the spending transaction can be propagated to other network nodes. A miner node can select to embed the valid spending transaction as part of a block that is added to the blockchain as described herein.

As shown in FIG. 3 , a blockchain compiler 1001 as described herein is used to translate a HLL program into a blockchain compatible script (or script fragment). This may be referred to as an “output script” as it may form the output provided by the blockchain compiler 1001. The output script may be provided in a blockchain transaction (Tx). It may be part of a locking script associated with a transaction output or part of the unlocking script associated with a transaction input. The output script may be formed of op_codes that are selected from, are native to, and/or form part of a blockchain scripting language which can be executed by the nodes of the blockchain network. The op_codes may be referred to as primitives or commands. The op_codes of the script can be executed 105 by an interpreter 104 or virtual machine that runs on the nodes of the blockchain network 1000. The interpreter or virtual machine may translate the op_codes of the script into machine-executable (object) code. The blockchain scripting language may be, for example, the Script language as used in conjunction with the Bitcoin protocol or a variation thereof. The scripting language may comprise cryptographic, arithmetic and stack manipulation op_codes.

The compiler 1001 can be part of an SDK or possibly an online service that employs static compilation to generate blockchain transaction scripts (or script fragments) that can be executed by bots or nodes of the blockchain network.

Alternatively, the methodology of the compiler as described herein can be used as part of the runtime environment of a bot or node of the blockchain network, where the runtime environment interprets or dynamically compiles or translates chunks of HLL programs (e.g., programs written in a 3G language such python, C++, etc.) into blockchain transaction script or script fragments that can be executed by the bot or node of the blockchain network.

FIG. 4 illustrates an exemplary blockchain protocol for validation and mining of a spending transaction 204 (labelled “TX 2”) that spends the output of a previous transaction 202 (labelled “TX1”). The previous transaction 202 has an output that includes a token amount (digital asset) and a locking script configured to define a set of conditions needed to spend the token amount. The previous transaction 202 has been validated and mined such that it is embedded in a block and then the block is verified such that it is stored on the blockchain 208. The spending transaction 204 includes an input with transaction output identifier fields (labelled “Tx output ID”) that refer to the output of the previous transaction 202 and an unlocking script. The locking script of the previous transaction 202 and the unlocking script of the spending transaction 204 are written using a low level functionally-restricted scripting language, such as Bitcoin's Script. For the spending transaction 204 to be considered valid, the unlocking script of the input must provide data that satisfies the set of conditions defined by the locking script of the referenced output of the previous transaction 202. The locking script of the previous transaction 202 (or part thereof) and the unlocking script of the spending transaction 204 can be generated by the blockchain compilation methods and tools as described herein.

The spending transaction 204 is validated by one or more nodes of the blockchain network (FIG. 4 ) by executing the unlocking script of spending transaction 204 together with executing the locking script of the previous transaction 202 in order to satisfy and validate a set of conditions dictated by the locking script of the previous transaction 202. The validation of the spending transaction 204 can involve other checks. Upon successful validation of the spending transaction 204, the spending transaction can be propagated to other network nodes. A miner node can perform mining operations that select and embed the valid spending transaction as part of a block that is added to the blockchain 208 as described herein. Once validated and stored on the blockchain 208, the sequence of transactions 202 and 204 provide for transfer of control over the token amount (digital assets) referenced by the transactions.

FIG. 5 is an illustrative, simplified block diagram of a computing device 2600 that may be used to practice at least one embodiment of the present disclosure. In various embodiments, the computing device 2600 may be used to implement the blockchain compiler and network nodes of the blockchain network as illustrated and described above. For example, the computing device 2600 may be configured for use as a data server, a web server, a portable computing device, a personal computer, or any electronic computing device. As shown in FIG. 5 , the computing device 2600 may include one or more processors 2602 that may be configured to communicate with, and are operatively coupled to, a number of peripheral subsystems via a bus subsystem 2604. The processors 2602 may be utilized for the compilation of an HLL source code program into a blockchain script (or fragment thereof) as described herein. These peripheral subsystems may include a storage subsystem 2606, comprising a memory subsystem 2608 and a file/disk storage subsystem 2610, one or more user interface input devices 2612, one or more user interface output devices 2614, and a network interface subsystem 2616. Such storage subsystem 2606 may be used for temporary or long-term storage of information, such as details associated with transactions described in the present disclosure.

The bus subsystem 2604 may provide a mechanism for enabling the various components and subsystems of computing device 2600 to communicate with each other as intended. Although the bus subsystem 2604 is shown schematically as a single bus, alternative embodiments of the bus subsystem may utilize multiple busses. The network interface subsystem 2616 may provide an interface to other computing devices and networks. The network interface subsystem 2616 may serve as an interface for receiving data from, and transmitting data to, other systems from the computing device 2600. For example, the network interface subsystem 2616 may enable a data technician to connect the device to a wireless network such that the data technician may be able to transmit and receive data while in a remote location, such as a user data centre. The bus subsystem 2604 may be utilized for communicating data such as details, search terms, and so on to the supervised model of the present disclosure, and may be utilized for communicating the output of the supervised model to the one or more processors 2602 and to merchants and/or creditors via the network interface subsystem 2616.

The user interface input devices 2612 may include one or more user input devices such as a keyboard; pointing devices such as an integrated mouse, trackball, touchpad, or graphics tablet; a scanner; a barcode scanner; a touch screen incorporated into the display; audio input devices such as voice recognition systems, microphones; and other types of input devices. In general, use of the term “input device” is intended to include all possible types of devices and mechanisms for inputting information to the computing device 2600. The one or more user interface output devices 2614 may include a display subsystem, a printer, or non-visual displays such as audio output devices, etc. The display subsystem may be a cathode ray tube (CRT), a flat-panel device such as a liquid crystal display (LCD), light emitting diode (LED) display, or a projection or other display device. In general, use of the term “output device” is intended to include all possible types of devices and mechanisms for outputting information from the computing device 2600. The one or more user interface output devices 2614 may be used, for example, to present user interfaces to facilitate user interaction with applications performing processes described and variations therein, when such interaction may be appropriate.

The storage subsystem 2606 may provide a computer-readable storage medium for storing the basic programming and data constructs that may provide the functionality of at least one embodiment of the present disclosure. The applications (programs, code modules, instructions), when executed by one or more processors, may provide the functionality of one or more embodiments of the present disclosure, and may be stored in the storage subsystem 2606. These application modules or instructions may be executed by the one or more processors 2602. The storage subsystem 2606 may additionally provide a repository for storing data used in accordance with the present disclosure. The storage subsystem 2606 may comprise a memory subsystem 2608 and a file/disk storage subsystem 2610.

The memory subsystem 2608 may include a number of memories, including a main random-access memory (RAM) 2618 for storage of instructions and data during program execution and a read only memory (ROM) 2620 in which fixed instructions may be stored. The file/disk storage subsystem 2610 may provide a non-transitory persistent (non-volatile) storage for program and data files and may include a hard disk drive, a floppy disk drive along with associated removable media, a Compact Disk Read Only Memory (CD-ROM) drive, an optical drive, removable media cartridges, and other like storage media.

The computing device 2600 may include at least one local clock 2624. The local clock 2624 may be a counter that represents the number of ticks that have transpired from a particular starting date and may be located integrally within the computing device 2600. The local clock 2624 may be used to synchronize data transfers in the processors for the computing device 2600 and all of the subsystems included therein at specific clock pulses and may be used to coordinate synchronous operations between the computing device 2600 and other systems in a data centre. In one embodiment, the local clock 2624 is an atomic clock. In another embodiment, the local clock is a programmable interval timer.

The computing device 2600 may be of various types, including a portable computer device, tablet computer, a workstation, or any other device described below. Additionally, the computing device 2600 may include another device that may be connected to the computing device 2600 through one or more ports (e.g., USB, a headphone jack, Lightning connector, etc.). The device that may be connected to the computing device 2600 may include a plurality of ports configured to accept fibre-optic connectors. Accordingly, this device may be configured to convert optical signals to electrical signals that may be transmitted through the port connecting the device to the computing device 2600 for processing. Due to the ever-changing nature of computers and networks, the description of the computing device 2600 depicted in FIG. 13 is intended only as a specific example for purposes of illustrating the preferred embodiment of the device. Many other configurations having more or fewer components than the system depicted in FIG. 5 are possible.

It should be noted that the above-mentioned embodiments illustrate rather than limit the present disclosure, and that those skilled in the art will be capable of designing many alternative embodiments without departing from the scope of the present disclosure as defined by the appended claims. The methods, systems and apparatus of the present disclosure (or parts thereof) may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In a device claim enumerating several means, several of these means may be embodied by one and the same item of hardware. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.

The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense. However, it will be evident that various modifications and changes may be made thereunto without departing from the scope of the invention as set forth in the claims. Likewise, other variations are within the scope of the present disclosure. Thus, while the disclosed techniques are susceptible to various modifications and alternative constructions, certain illustrated embodiments thereof are shown in the drawings and have been described above in detail. It should be understood, however, that there is no intention to limit the invention to the specific form or forms disclosed but, on the contrary, the intention is to cover all modifications, alternative constructions and equivalents falling within the scope of the invention, as defined in the appended claims.

In the claims, any reference signs placed in parentheses shall not be construed as limiting the claims. Furthermore, the use of the terms “a” and “an” and “the” and similar referents in the context of describing the disclosed embodiments (especially in the context of the following claims) is to be construed to cover both the singular and the plural, unless otherwise indicated or clearly contradicted by context. The terms “comprising”, “having”, “including”, and “containing” are to be construed as open-ended terms (i.e., meaning “including, but not limited to”) unless otherwise noted. The term “connected”, when unmodified and referring to physical connections, is to be construed as partly or wholly contained within, attached to or joined together, even if there is something intervening. Recitation of ranges of values in the present disclosure are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range unless otherwise indicated and each separate value is incorporated into the specification as if it were individually recited. The use of the term “set” (e.g., “a set of items”) or “subset”, unless otherwise noted or contradicted by context, is to be construed as a nonempty collection comprising one or more members. Further, unless otherwise noted or contradicted by context, the term “subset” of a corresponding set does not necessarily denote a proper subset of the corresponding set, but the subset and the corresponding set may be equal. The singular reference of an element does not exclude the plural reference of such elements and vice-versa.

Conjunctive language, such as phrases of the form “at least one of A, B, and C”, or “at least one of A, B and C”, unless specifically stated otherwise or otherwise clearly contradicted by context, is otherwise understood with the context as used in general to present that an item, term, etc., may be either A or B or C, or any nonempty subset of the set of A and B and C. For instance, in the illustrative example of a set having three members, the conjunctive phrases “at least one of A, B, and C” and “at least one of A, B and C” refer to any of the following sets: {A}, {B}, {C}, {A, B}, {A, C}, {B, C}, {A, B, C}. Thus, such conjunctive language is not generally intended to imply that certain embodiments require at least one of A, at least one of B and at least one of C each to be present.

Operations of processes described can be performed in any suitable order unless otherwise indicated or otherwise clearly contradicted by context. Processes described (or variations and/or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions and may be implemented as code (e.g., executable instructions, one or more computer programs or one or more applications) executing collectively on one or more processors, by hardware or combinations thereof. The code may be stored on a computer-readable storage medium, for example, in the form of a computer program comprising a plurality of instructions executable by one or more processors. The computer-readable storage medium may be non-transitory.

The use of any and all examples, or exemplary language (e.g., “such as”) provided, is intended merely to better illuminate embodiments of the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.

Embodiments of this disclosure are described, including the best mode known to the inventors for carrying out the invention. Variations of those embodiments may become apparent to those of ordinary skill in the art upon reading the foregoing description. The inventors expect skilled artisans to employ such variations as appropriate and the inventors intend for embodiments of the present disclosure to be practiced otherwise than as specifically described. Accordingly, the scope of the present disclosure includes all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. Moreover, any combination of the above-described elements in all possible variations thereof is encompassed by the scope of the present disclosure unless otherwise indicated or otherwise clearly contradicted by context.

All references, including publications, patent applications, and patents, cited are hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety. 

The invention claimed is:
 1. A computer-implemented method comprising steps: receiving a portion of a source code as input, wherein the portion of the source code is written in a high-level language (HLL) that specifies a functionality; and generating an output script comprising a plurality of op codes selected from and/or native to a functionally-restricted blockchain scripting language such that, when executed, the output script provides, at least in part, a functionality specified in the portion of the source code, wherein the functionally-restricted blockchain scripting language does not natively support complex control-flow constructs, recursion, and jump-based loops.
 2. The computer-implemented method of claim 1, and further comprising the step of: providing or using a compiler arranged to perform the steps of claim
 1. 3. The computer-implemented method of claim 2, wherein the compiler forms part of a software development kit (SDK).
 4. The computer-implemented method of claim 1, wherein the output script is generated by performing a static compilation.
 5. The computer-implemented method of claim 1, wherein the step of generating the output script comprises: unrolling at least one looping construct provided in the portion of the source code.
 6. The computer-implemented method of claim 1, and further comprising the step of: providing or using an interpreter or a virtual machine arranged to convert the output script into a form that is executable on a blockchain platform.
 7. The computer-implemented method of claim 1, and further comprising the step of: optimising the output script at least once to provide a more efficient or reduced version of the output script.
 8. The computer-implemented method of claim 1, wherein the step of generating the output script comprises derivative free optimisation.
 9. The computer-implemented method of claim 1, wherein the portion of the source code is arranged to implement a smart contract.
 10. The computer-implemented method of claim 1, wherein the HLL comprises at least one primitive or construct which can be translated directly into one or more primitives native to the functionally-restricted blockchain scripting language.
 11. The computer-implemented method of claim 1, wherein the functionally-restricted blockchain scripting language is stack-based and the HLL comprises one or more primitives arranged to perform an operation on a stack used by the functionally-restricted blockchain scripting language.
 12. The computer-implemented method of claim 1, wherein the HLL comprises a primitive arranged to push a number of inputs to the portion of the source code onto a stack used for memory allocation by the functionally-restricted blockchain scripting language.
 13. The computer-implemented method of claim 1, wherein the HLL comprises at least one of the following primitives or operators or a functional equivalent of at least one of the following primitives or operators: Initiate; Declare; Increment; IF; While; Populate; Monus; Reset; Rawscript; Abort; Retrieve; and Hash, hash 160, or another hash operation or a variation thereof.
 14. A computer-implemented system comprising one or more processors and a memory that stores computer-executable instructions that, as a result of execution, cause the one or more processors to implement the steps of claim
 1. 15. The computer-implemented system of claim 14, further comprising a compiler arranged to: receive a portion of the source code as input, the portion of the source code being written in a high-level language (HLL) and specifying a functionality; and generate an output script comprising a plurality of op codes selected from a functionally-restricted blockchain scripting language such that, when executed, the output script provides, at least in part, the functionality specified in the portion of the source code, wherein the functionally-restricted blockchain scripting language does not natively support complex control-flow constructs, recursion, and jump-based loops.
 16. The computer-implemented system of claim 14, further comprising a software development kit (SDK).
 17. A computer-implemented method comprising the step of using static compilation to translate a portion of source code into a blockchain-compatible script, wherein the blockchain-compatible script is functionally-restricted and does not natively support complex control-flow constructs, recursion, and jump-based loops, and wherein the static compilation comprises the step of loop unrolling. 